A Neural Network Optimization Model-Based Approach to Evaluate the Teaching Effectiveness of English Courses

The improvement of teaching quality is an essential part of modernization of Chinese education, and the scientific, rational and timely improvement of teaching effectiveness assessment plays a key role. The improvement of scientific and timely teaching effectiveness evaluation plays a key role. This paper takes artificial intelligence technology as the leading to address the problem of low accuracy of university English teaching effectiveness evaluation, a evaluation method based on IGA-WNN is proposed. Firstly, an English course teaching evaluation system was established according to the actual teaching situation, and the entropy method (EM) was used to assign weights to the original teaching evaluation effect data, then an English course teaching evaluation model was designed based on wavelet neural network, and an improved genetic algorithm was studied to optimize the wavelet neural network parameters. The experimental results show that the method can evaluate the quality of English teaching more accurately and has a good educational support function.